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http://dx.doi.org/10.5351/KJAS.2017.30.6.983

Functional ARCH (fARCH) for high-frequency time series: illustration  

Yoon, J.E. (Department of Statistics, Sookmyung Women's University)
Kim, Jong-Min (Statistics Discipline, University of Minnesota-Morris)
Hwang, S.Y. (Department of Statistics, Sookmyung Women's University)
Publication Information
The Korean Journal of Applied Statistics / v.30, no.6, 2017 , pp. 983-991 More about this Journal
Abstract
High frequency time series are now prevalent in financial data. However, models need to be further developed to suit high frequency time series that account for intraday volatilities since traditional volatility models such as ARCH and GARCH are concerned only with daily volatilities. Due to $H{\ddot{o}}rmann$ et al. (2013), functional ARCH abbreviated as fARCH is proposed to analyze intraday volatilities based on high frequency time series. This article introduces fARCH to readers that illustrate intraday volatility configuration on the KOSPI and the Hyundai motor company based on the data with one minute high frequency.
Keywords
fARCH; high frequency; intraday volatility;
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Times Cited By KSCI : 2  (Citation Analysis)
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